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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Communication in Biomathematical Sciences JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) eProceedings of Engineering Jurnal INFOTEL Cahaya Pengabdian
Aditya Firman Ihsan
Telkom University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

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Javanese Script Letter Detection Using Faster R-CNN Muhammad Helmy Faishal; Mahmud Dwi Sulistiyo; Aditya Firman Ihsan
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 2 (2023): September 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i2.24641

Abstract

The Javanese script is now rarely used, and some people no longer recognize it. The construction of a Javanese script recognition system based on digital image processing is one of its preservation efforts. This study proposes a model capable of detecting and recognizing Javanese characters using Faster R-CNN to help people who are not familiar with the Javanese script. Faster R-CNN was chosen because it does not require additional processing compared to the previous method and Faster R-CNN has better accuracy and the ability to detect small objects. Faster R-CNN shows good results in text detection, but the use of Faster R-CNN in detecting Javanese script has not been found which makes its performance unknown, so this study will show how Faster R-CNN performs in detecting Javanese script. In this study, Faster R-CNN was able to show good performance by obtaining mean average precision (mAP) values up to 0.8381, accuracy up to 96.31%, precision up to 96.53%, recall up to 96.38 %, and F1-Score up to 96.41%. These results indicate that Faster R-CNN has better results than the previous method and can detect Javanese characters well.
Co-Authors Alif Adwitiya Pratama Andi Fadil Adiyaksa Conny Tria Shafira Djatnika Widia Nugraha Donni Richasdy Donny Richasdy Hery Widijanto Indidharmanto, Ahmad Maulana Made Mita Wikantari Mahmud Dwi Sulistiyo Muhammad Daffa Regenta Sutrisno Muhammad Helmy Faishal Muzakky, Faqih Ahmad Puteri, Nurhidayah Putra, Rachmat Dwi Putu Harry Gunawan Raisa Benaya Rheza Ramadhan Putra Shuhaimi Mahadzir Sri Suryani Prasetiyowati Sujadi, Cika Carissa Sulistyo, Mahmud Dwi Uruqul Nadhif Dzakiy Widi Astuti Yuliant Sibaroni Yusuf, Afrizal Syahruluddin